Hydroclimatic Variability and Predictability: A Survey of Recent Research

Abstract

This is a somewhat unusual but useful format for a scientific paper, as explained by the authors: not intented as an extensive review of the dynamic field of research in hydrometeorological predictions, but an instructive topical description of some relevant aspects of the scientific field, illustrated by studies which were presented at Eric Woods honor symposium. The body of the paper is well written an well structured, but the degree to which the selected studies are self-explanatory varies somewhat at could be improved (see detailed comments below). Some figures showed very interesting results (8, 10, 11). Detailed comments C1

Disentangling Drivers of Meteorological Droughts in the European Greater Alpine Region During the Last Two Centuries

“…Figure ) and secondly because RR efficiency is found to be lower in the warm season as compared to the cold season in the recent 40 years. Although soil moisture‐precipitation feedbacks are not straightforward to identify (Koster et al, ; Tuttle & Salvucci, ), our findings are in line with other studies (Findell et al, ; Guillod et al, ) who found evidence for a positive feedback during the warm season as well. Considering moisture sources for the Alpine region in particular, using a Lagrangian moisture source diagnostics model, Sodemann and Zubler () found that there are distinct differences between seasons, with DJF precipitation being mostly driven by large‐scale advection (continental moisture recycling <10%) and JJA precipitation showing considerably higher continental recycling rates of up to 50%, highlighting the importance of soil moisture precipitation feedbacks.…”

“…For events in the warm season (1971, 1976, and 2003), the mean frequency anomaly of ACTs is 1.34 and the mean precipitation efficiency is 0.88, which is considerably lower than the respective values of the cold season events. Due to the convective characteristics of JJA time precipitation formation, local conditions of moisture sources (soil) are of higher importance, which in turn leads to lower precipitation efficiency if soil moisture states are already low from preceding MAM (Koster et al, ; van der Linden et al, ). This process was of particular importance in the 2003 event, which started in late DJF, exhibited positive frequency anomalies of ACTs during MAM (1.94 in MAM) leading to soil moisture deficits in early JJA and then through a soil moisture atmosphere coupling to considerably low precipitation efficiency (0.54 in JJA).…”

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

“…Meanwhile, regional land surface characteristics (e.g., soil moisture, vegetation, snow cover) have also been shown to strengthen or weaken drought severity and affect drought development (Koster et al, ; Schubert et al, ; Su & Dickinson, ; Yuan & Wood, ). Soil moisture, for instance, may contribute to the weather (or climate) prediction either through its direct impact on the water and energy balance, or through its memory characteristic affecting atmospheric variability and land surface hydrology (Evans et al, ; Koster et al, ; Nicolai‐Shaw et al, ; Seneviratne et al, ).…”

“…For example, the land‐atmospheric interactions or feedbacks, which have been shown to be important factors for drought occurrence, have not been fully understood and reproduced by GCMs (Taylor et al, ). Thus, a pressing need is to improve the atmospheric and land models to incorporate key processes related to extremes, which involve increasing model resolutions and parameterizing subgrid scale processes with novel approaches (Koster et al, ; WCRP, ). Moreover, many processes related to human activities, such as pumping, irrigation, land use change, urbanization, and deforest, are not well quantified and have rarely been included in either offline hydrologic models or coupled climate forecast system.…”

Long-term ensemble forecast of snowmelt inflow into the Cheboksary reservoir under the differently constructed weather scenarios

“…Additionally, on the basis of processoriented hydrological models, an opportunuty appears for long-term forecasting of the internal hydrological variables other 10 than runoff (snow, soil moisture, etc.) (see comprehensive review presented by Koster et al, 2017). At the same time, despite significant achievements in long-term forecasting methodology, the forecasts are still far from perfection and implementation of the state-of-the-art methods into practice should be carried out with extensive testing.…”